SCHRES-06733; No of Pages 7 Schizophrenia Research xxx (2016) xxx–xxx

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Cognitive insight is associated with cortical thickness in first-episode psychosis Lisa Buchy a, Mariapaola Barbato a, Frank P. MacMaster b,c,e, Signe Bray d, Darren Clark a, Stephanie Deighton a, Jean Addington a,⁎ a

Hotchkiss Brain Institute, Department of Psychiatry, University of Calgary, Alberta, Canada Department of Psychiatry, University of Calgary, Alberta, Canada Strategic Clinical Network for Addictions and Mental Health, Alberta Health Services, Alberta, Canada d Department of Radiology and Pediatrics, University of Calgary, Alberta, Canada e Department of Pediatrics, University of Calgary, Alberta, Canada b c

a r t i c l e

i n f o

Article history: Received 12 December 2015 Received in revised form 10 February 2016 Accepted 13 February 2016 Available online xxxx Keywords: Cognitive bias Diffusion tensor imaging Magnetic resonance imaging Schizophrenia Self-certainty Self-reflectiveness

a b s t r a c t Compared to non-clinical subjects, people with psychosis show poor cognitive insight as reflected in low SelfReflectiveness and high Self-Certainty. Neuroimaging studies have reported that 1) low Self-Reflectiveness is associated with volumetric reductions in ventrolateral prefrontal cortex (VLPFC), 2) higher Self-Certainty is associated with volumetric reductions in hippocampus, and 3) higher Self-Certainty is associated with fractional anisotropy in the fornix, in people with psychosis. The aims of the current study were to expand on this research by 1) performing an exploratory whole-brain cortical thickness analysis of the neural correlates of cognitive insight, to reveal whether regions outside the VLPFC are important for cognitive insight, and 2) to evaluate associations between cognitive insight and subfields of the hippocampus, which are distinct, interacting, and have different functions. We also aimed to replicate previous research documenting associations between cognitive insight and 3) total hippocampal volumes and 4) fornix fractional anisotropy. Fifteen people with a firstepisode psychosis completed the Beck Cognitive Insight Scale and provided magnetic resonance and diffusion tensor imaging scans. Cortical thickness and hippocampal volumes were analyzed in FreeSurfer, and fornixfractional anisotropy was analyzed in Diffusion Toolkit/TrackVis. Higher Self-Reflectiveness and lower SelfCertainty significantly associated with thickness and thinness in VLPFC, respectively, as well as thickness and thinness in widespread frontal, parietal and temporal cortices. No associations emerged between SelfReflectiveness or Self-Certainty and hippocampal total or sub-field volumes, or fornix fractional anisotropy. Results suggest that the neural correlates of cognitive insight involve a network of frontal, temporal and parietal brain regions. © 2016 Published by Elsevier B.V.

1. Introduction People with psychosis show well-documented biases in reasoning, such as the tendency to ‘jump to conclusions’ (Garety et al., 1991), attribute failure to others (Fornells-Ambrojo and Garety, 2009) and make hasty decisions under conditions of uncertainty (Moritz et al., 2009), among others. In 2004, Beck and colleagues developed the self-report Beck Cognitive Insight Scale to psychometrically assess how people with psychosis understand their reasoning biases and atypical interpretation of events (Beck et al., 2004). Over a decade later, it is now documented that compared to non-clinical subjects, people with psychosis show poorer cognitive insight as reflected by decreased Self-Reflectiveness (willingness to acknowledge fallibility, corrigibility, and ⁎ Corresponding author at: Mathison Centre for Mental Health Research & Education, University of Calgary, 3280 Hospital Drive NW, Calgary, Alberta T2N 4Z6, Canada. E-mail address: [email protected] (J. Addington).

recognition of dysfunctional reasoning), and increased Self-Certainty (overconfidence in beliefs) (Riggs et al., 2010). Impairments in cognitive insight have been associated with more severe positive symptoms (Buchy et al., 2009; Engh et al., 2009; Warman et al., 2007), and poorer verbal memory (Buchy et al., 2010b; Engh et al., 2011; Lepage et al., 2008; Orfei et al., 2010) and executive functioning (Cooke et al., 2010; Orfei et al., 2010). There is some evidence that people with psychosis with higher cognitive insight are more likely to be living independently (Favrod et al., 2008) and that cognitive insight improves alongside reductions in positive symptoms following cognitive behavioral therapy (Penn et al., 2009; Perivoliotis et al., 2010). This form of insight can be distinguished from clinical insight, in which a clinician rates an individual's awareness of his or her mental illness, the efficacy of treatment, and awareness and attribution of symptoms (Amador et al., 1993; David et al., 1992). Research has now begun to evaluate the neural substrates of cognitive insight in people with psychosis. A first study to evaluate the

http://dx.doi.org/10.1016/j.schres.2016.02.026 0920-9964/© 2016 Published by Elsevier B.V.

Please cite this article as: Buchy, L., et al., Cognitive insight is associated with cortical thickness in first-episode psychosis, Schizophr. Res. (2016), http://dx.doi.org/10.1016/j.schres.2016.02.026

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structural neural correlates of cognitive insight in a first-episode of psychosis (FEP) sample reported that higher Self-Certainty associated with smaller total hippocampal volumes (Buchy et al., 2010b). A second study reported that higher fractional anisotropy in the fornix, the main output pathway of the hippocampus, correlated with higher Self-Certainty in a FEP sample (Buchy et al., 2012b). Another study showed that higher Self-Reflectiveness correlated with increased volume in right ventrolateral prefrontal cortex (VLPFC) in people with schizophrenia (Orfei et al., 2013). Increased cortical thickness in VLPFC has also been correlated with higher Self-Reflectiveness in a nonclinical sample (Buchy and Lepage, 2015). Functional neuroimaging pursuits have provided complementary evidence that higher SelfReflectiveness is associated with increased neural activation in VLPFC (Buchy et al., 2015; Orfei et al., 2013; Pu et al., 2013) in psychosis. This research suggests that the VLPFC, hippocampus, and fornix may form in part the brain systems that support cognitive insight in people with psychosis. Given the small number of investigations, further studies are needed to strengthen the hypothesis that these brain regions are components of the neural circuitry of cognitive insight in psychosis. There are several limitations in the existing literature. First, some studies evaluated brain structure in individuals with chronic schizophrenia, introducing potential confounds of lengthy medication use, stigma, and hospitalization, among others. Second, some studies used volumetric techniques such as voxel-based morphometry to evaluate volumes of the VLPFC, rather than more sensitive neuroanalytic tools such as analysis of cortical thickness which has been validated with post mortem data (Fischl and Dale, 2000). Cortical thickness provides a fully automated, objective measure of neuroanatomy and provides a metric in millimeters of gray matter morphology, reflecting cortical laminar structure and integrity. The technique allows separate assessment of cortical thickness and surface area, which appear to be under separate genetic control (Panizzon et al., 2009; Rakic, 1995). Voxel-based morphometry is sensitive to registration differences, size of the smoothing kernel, shape differences that arise from systematic registration errors during spatial normalization, and image noise (Bookstein, 2001; Jones et al., 2005). Additionally, blurring is 3 dimensional in VBM and therefore does not respect boundaries along tissue classes, leading to increased probability of either diluting existing signal or misinterpreting boundary shift as signal. Comparatively, blurring in cortical thickness analysis occurs in a topographically correct manner along the cortical surface. Increased cortical thickness in VLPFC has also been correlated with higher SelfReflectiveness in a non-clinical sample (Buchy and Lepage, 2015). Third, we aim to expand on previous studies by using a vertex-wide approach to measure associations between cognitive insight and cortical thickness across the entire cerebrum. Looking only at the VLPFC forfeits examination of possible cortical alterations in other frontal and more posterior brain regions underlying cognitive insight, such as temporal and parietal cortices, which have been associated with other aspects of insight including individual's awareness of their mental disorder (Parellada et al., 2011), awareness of the need for treatment (Buchy et al., 2011), attribution of symptoms (Shad et al., 2006), and ability to monitor changes in one's state of mind and one's sensation (Spalletta et al., 2014). Fourth, the only study to evaluate the relation between cognitive insight and the hippocampus evaluated total hippocampal volumes. Recent advances in imaging analysis now allow for the extraction of a number of distinct and interacting subfields of the hippocampus (Iglesias et al., 2015). A body of animal research has shown that hippocampal subfields have different functions in memory (Acsady and Kali, 2007; Hunsaker et al., 2008; Kesner, 2013; Schmidt et al., 2012), are believed to be involved differentially in learning and memory in humans (Acsady and Kali, 2007; Gabrieli et al., 1997; Kesner, 2007, 2013; Knierim et al., 2006), and are affected differentially by aging (Harding et al., 1998; Simic et al., 1997; Thal et al., 2000). The aims of the present study were to expand on previous research by 1) performing a novel and exploratory analysis of the neural

correlates of cognitive insight using a vertex-wise approach across the entire cerebrum, and 2) performing a novel correlational analysis between cognitive insight and hippocampal subfield volumes, in a FEP sample. We further aimed to replicate previous research showing associations between cognitive insight and 3) total hippocampal volumes and 4) fractional anisotropy of the fornix, in people with a FEP. Our hypotheses for these four aims were: 1) higher Self-Reflectiveness would correlate with cortical thickness in VLPFC, as well as in parietal and temporal cortices; 2) higher Self-Certainty would associate with smaller hippocampal sub-field volumes; 3) higher Self-Certainty would correlate with smaller bilateral total hippocampal volumes; and 4) higher Self-Certainty would correlate with increased fractional anisotropy in the fornix. 2. Materials and methods 2.1. Participants Participants were recruited through the Early Psychosis Program at the Foothills Hospital in Calgary. For this study a FEP was defined as being within the first three years of receiving an initial diagnosis of a psychosis and confirmed through chart records. Fifteen participants completed the Beck Cognitive Insight Scale and provided magnetic resonance imaging (MRI) anatomical scans and DTI scans. Twelve participants were taking anti-psychotic medications at the time of the study. Exclusion criteria were history of neurological disorder, head trauma causing loss of consciousness, or presence of metal in the body. All participants provided written informed consent and the study was approved by the University of Calgary Conjoint Health Research Ethics Board. 2.2. Measures Severity of symptoms was assessed using the Positive and Negative subscales of the Positive and Negative Syndrome Scale (PANSS) (Kay et al., 1987). Ratings were conducted by experienced research clinicians. Cognitive insight was measured with the 15-item self-report Beck Cognitive Insight Scale (Beck et al., 2004). Self-Reflectiveness and SelfCertainty scores were computed. Each question is rated on a 4-point scale from 0 (does not agree at all) to 3 (agree completely), with higher scores indicating higher Self-Reflectiveness and Self-Certainty. IQ was estimated with the Vocabulary and Block Design subtests of the Wechsler Abbreviated Scale of Intelligence (Wechsler, 1999). 2.3. Scanning procedures 2.3.1. MRI and DTI acquisition Scanning was carried out at the Seaman MRI Centre at Calgary Foothills Hospital on a 3 T General Electric whole body MRI system with a 12-channel head coil. Sequence parameters were optimized for the scanner manufacturer, software version and coil configuration according to the ADNI protocol (http://adni.loni.usc.edu/methods/researchtools/). Scans were acquired in the sagittal plane with a 1 mm × 1 mm in-plane resolution and 1.2 mm slice thickness. A Magnetization Prepared Rapid Gradient Echo (MPRAGE) sequence was used with a 256 (axial) × 240 (sagittal) × 176 (coronal) mm field of view, repetition time = 2300 ms, echo time = 2.91, inversion time = 900 ms with a flip angle = 9°. DTI images were acquired using a single-shot echo planar imaging sequence parallel to the anterior–posterior commissural plane. Diffusion sensitive gradients were applied in 31 non-collinear, noncoplanar directions (b0 = 5, b = 1000 s/mm2). The acquisition parameters were as follows: TR = 15,050 ms, TE = 81.6 ms, and image matrix 128 × 128. These parameters resulted in 2.9 × 2.9 × 2.9 mm3 acquisition voxel dimensions.

Please cite this article as: Buchy, L., et al., Cognitive insight is associated with cortical thickness in first-episode psychosis, Schizophr. Res. (2016), http://dx.doi.org/10.1016/j.schres.2016.02.026

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2.3.2. Cortical thickness measurement FreeSurfer image analysis package was used to model cortical thickness from each participant's T1-weighted MRI (http://surfer.nmr.mgh. harvard.edu). In summary, this automated procedure via recon-all pipeline includes image intensity normalization, removal of non-brain tissues, segmentation of gray/white matter and subcortical volumetric structures, tessellation of the gray/white matter boundary, topology correction, spherical surface-based inter-subject registration based on the cortical surface curvature (sulci and gyri) and automated parcellation of brain regions. Detailed procedures can be found in previous publications (Fischl and Dale, 2000; Fischl et al., 2002; Fischl et al., 1999). A post-processing visual inspection for quality was conducted and manual corrections were performed if necessary. Local cortical thickness was measured based on the difference between the position of equivalent vertices in the pial and gray/white matter surfaces. ROI regions were defined using the Desikan–Killiany atlas in FreeSurfer. The subcortical segmentation procedure assigns a neuroanatomic label to each voxel of the MRI volume using a probabilistic atlas and a Bayesian classification rule. 2.4. Imaging analyses 2.4.1. Cortical thickness The Query Design Estimate Contrast (QDEC) application of FreeSurfer was used to carry out a general linear model analysis at each vertex of the cortical surface. Data were smoothed on the surface using a Gaussian smoothing kernel with a full-width halfmaximum = 10 mm. The association between cognitive insight and cortical thickness was investigated using multiple regression analyses after adjusting both variables for age. For these analyses, cortical thickness was the dependent variable, scores on Self-Reflectiveness and SelfCertainty were explanatory variables, and age was entered as a covariate. Positive and negative correlations were performed indicating regions where higher scores on Self-Reflectiveness and Self-Certainty associated with cortical thickness and thinness, respectively. A false discovery rate of 0.01 was applied to correct for multiple comparisons at the vertex level. 2.4.2. Hippocampus Total hippocampal volumes were extracted from the aseg.volume stats data import in FreeSurfer. Hippocampal subfields were segmented in FreeSurfer (Iglesias et al., 2015). This tool generates an automated segmentation of the hippocampus using a statistical atlas built largely upon ultra-high resolution (~ 0.1 mm isotropic) ex vivo MRI data. Mean volumes were extracted for the following regions bilaterally: presubiculum, CA1, CA2/3, fimbria, subiculum, CA4/Dentate gyrus, hippocampal fissure, and hippocampus (most caudal and rostral portions of the formation which cannot be further divided into subfields). 2.4.3. Fornix Diffusion tensors were fitted at each voxel from the diffusion weighted imaging data, using a DTI fit model. Deterministic whole brain tractograms were reconstructed from tensors using a 2nd order Runge–Kutta method. In addition, whole-brain scalar fractional anisotropy and fractional anisotropy-weighted color maps were generated for each participant. Two regions of interest (ROI) were drawn on fractional anisotropy-weighted color maps. ROI locations were adapted from Concha et al. (2005) using a published protocol (Buchy et al., 2012b; Luck et al., 2011). The first ROI was placed on the most inferior axial slice in which the crus of the fornix was visible (Fig. 2a). The second ROI was placed on the coronal slice in which the cerebral peduncles were most visible (Fig. 2b). Fibers inferior to the corpus callosum were selected as the second ROI. ROI radii ranged from 5 to 12 for the first ROI and was set to 12 for the second ROI. Each fiber passing through the two ROIs of each tract was selected and mean fractional anisotropy values were extracted for left and right fornix. Fig. 2c shows a

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representative example of the isolated bilateral fornix. All analyses were performed using Diffusion Toolkit version 0.6.3 and TrackVis version 0.6.0.1 (Wang et al., 2007). 2.4.4. Inter-rater and intra-rater reliabilities for fornix tractography For intra-rater reliability, a subset of five subjects randomly selected was replicated twice by one rater. For inter-rater reliability, tractographies were performed by another rater on the same subset, and fractional anisotropy values were compared between and within raters. Inter-rater and intra-rater correlations reached 0.94 and 0.99 for the left fornix respectively, and 0.99 and 0.99 for the right fornix respectively. 2.5. Statistical analyses All variables were visually inspected for statistical outliers, and outliers ≥2 standard deviations from the mean were removed. The association between hippocampal structure and fornix fractional anisotropy, and Self-Reflectiveness and Self-Certainty scores was investigated using partial correlations, with age entered as a covariate, and with intracranial volume as an additional covariate in volumetric analyses. The critical p-value was corrected to p = 0.05/40 = 0.001 for analyses involving the hippocampus and fornix (20 regions × 2 cognitive insight variables as shown in Table 2). These variables were analyzed with SPSS 22.0. 2.6. Procedures Participants completed the Beck Cognitive Insight Scale, underwent MR and DTI scans, and were then rated on demographic and clinical variables by experienced research clinicians. 3. Results 3.1. Demographic and clinical characteristics Table 1 displays clinical and demographic characteristics, and cognitive insight scores of the sample. Self-Certainty and Self-Reflectiveness were not significantly correlated, r = − 0.40, p = 0.16, and neither Self-Reflectiveness or Self-Certainty significantly correlated with PANSS total positive symptoms nor total negative symptoms, r = −0.42, p = 0.12, and r = 0.14, p = 0.63, respectively. Table 1 Demographic and clinical characteristics of the sample.

Age Years of education PANSS total positive symptoms PANSS total negative symptoms Antipsychotic dosagea IQ Beck Cognitive Insight Scale Self-Reflectiveness Self-Certainty

Mean (SD)

Range

22.7 (2.6) 13.4 (2.1) 14.7 (7.5) 12.6 (3.5) 234.1 (320.8) 107.9 (11.1)

19–27 12–18 7–30 7–19 0–1232 91–125

16.1 (3.6) 6.4 (2.3)

10–23 2–11 N (%)

Gender (M:F) Handedness Right Left Diagnosis Schizophrenia Psychosis not otherwise specified Brief psychotic disorder Delusional disorder

13 (87.0) 2 (13.0) 14 (93.0) 1 (7.0) 10 (67.0) 3 (21.0) 1 (7.0) 1 (7.0)

Note. PANSS = Positive and Negative Syndrome Scale. a Measured in chlorpromazine equivalents.

Please cite this article as: Buchy, L., et al., Cognitive insight is associated with cortical thickness in first-episode psychosis, Schizophr. Res. (2016), http://dx.doi.org/10.1016/j.schres.2016.02.026

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3.1.1. Correlations of cortical thickness with cognitive insight As shown in Fig. 1, regression analysis indicated significant associations between higher Self-Certainty and thinner cortex in widespread frontal, temporal and parietal and occipital regions. Significant associations also can be seen between higher Self-Reflectiveness and thicker cortex in frontal, temporal, parietal and occipital loci. Complete results of all brain regions that were significantly associated with SelfReflectiveness and Self-Certainty are shown in Supplementary Table 1 and Supplementary Table 2. 3.2. Correlations of hippocampus and fornix with cognitive insight Means, standard deviations and ranges for hippocampal volumes and fornix fractional anisotropy are displayed in Table 2. Correlations between cognitive insight and total hippocampus and subfield volumes and fornix fractional anisotropy are shown in Table 3. 3.2.1. Hippocampus Partial correlational analyses revealed no significant associations between either Self-Reflectiveness or Self-Certainty and total hippocampal volumes, or volumes of hippocampal subfields. 3.2.2. Fornix The two ROIs of the fornix could not be located on their fractional anisotropy color map for one participant; therefore, this person was excluded from this analysis. All partial correlations between SelfReflectiveness and Self-Certainty with left and right fornix were nonsignificant. 4. Discussion The current study found significant associations between SelfReflectiveness and Self-Certainty scores and cortical thickness in VLPFC as well as widespread frontal, parietal and temporal cortices, providing support for our first hypothesis. No significant associations emerged between Self-Certainty scores and hippocampal total or subfield volumes; thus hypotheses two and three were not supported. Our fourth hypothesis was not supported as no significant associations were seen between Self-Certainty and fractional anisotropy of the fornix.

Table 2 Means, standard deviations and ranges for number of volumes for total hippocampus and sub-fields, and fractional anisotropy of the fornix. Structure Volumes Total hippocampus Presubiculum CA1 CA2/3 Fimbria Subiculum CA4 Hippocampal fissure Hippocampusa Total hippocampus Presubiculum CA1 CA2/3 Fimbria Subiculum CA4 Hippocampal fissure Hippocampusa Fractional anisotropy Fornix Fornix

Hemisphere

Mean

SD

Minimum

Maximum

Left Left Left Left Left Left Left Left Left Right Right Right Right Right Right Right Right Right

3938.0 472.2 322.8 933.0 57.0 615.1 516.5 39.0 348.9 3986.9 432.2 331.9 982.5 45.4 588.3 539.7 53.4 370.2

445.2 56.1 42.8 111.2 24.4 66.3 64.3 14.7 51.1 467.2 53.2 50.1 98.3 15.0 82.0 58.3 15.6 104.8

3196.3 356.5 265.9 769.7 32.7 468.3 409.7 19.3 263.8 2860.4 327.6 246.2 802.8 24.1 411.0 440.2 35.9 102.4

4675.6 550.3 409.2 1145.5 114.7 713.0 647.0 70.1 452.2 4625.7 503.1 445.0 1163.6 79.9 742.8 649.7 92.7 507.6

Left Right

0.38 0.38

0.03 0.02

0.34 0.35

0.42 0.42

Note. Hippocampal volumes are in cubic mm. a Most caudal and rostral portions of the formation which cannot be further divided into subfields.

The current analysis revealed associations between thickness in VLPFC and Self-Reflectiveness and Self-Certainty in people with a FEP. These results are consistent with a recent report in non-clinical subjects, in which Self-Certainty was significantly associated with thickness in VLPFC (Buchy and Lepage, 2015), and with functional imaging studies showing significant associations between neural structure in VLPFC and Self-Reflectiveness (Orfei et al., 2013), and between VLPFC and Self-Reflectiveness (Buchy et al., 2010b; Pu et al., 2013). These findings complement the results of a study that has linked the VPFC to cognitive flexibility and specifically the capacity to generate flexible behavior in social contexts (Nelson and Guyer, 2011). Results of this study fit with results suggesting that the VLPFC may integrate cognitive and motivational information to guide flexible goal-directed behavior (Sakagami

Fig. 1. Cortical thickness statistic maps showing regression against cortical thickness with A) Self-Reflectiveness and B) Self-Certainty. Red and yellow indicate positive associations and blue indicates negative associations. Widespread associations can be seen between greater cortical thickness in frontal, temporal and parietal regions with higher Self-Reflectiveness and lower Self-Certainty. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Please cite this article as: Buchy, L., et al., Cognitive insight is associated with cortical thickness in first-episode psychosis, Schizophr. Res. (2016), http://dx.doi.org/10.1016/j.schres.2016.02.026

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Fig. 2. Regions of interest to define the fornix adapted from Concha et al. (2005). A) The first ROI was placed on the most inferior axial slice in which the crus of the fornix was visible; B) the second ROI was placed on the coronal slice in which the cerebral peduncles were most visible; C) representative example of the isolated bilateral fornix.

and Pan, 2007), and/or control access to stored conceptual representations (Badre and Wagner, 2007; Levy and Wagner, 2011). As proposed in a sample of non-clinical subjects (Buchy and Lepage, 2015), these functions may relate to cognitive insight in FEP, such that one's capacity to form appropriate confidence levels and critically reflect on errors in thinking may partially depend on controlled retrieval of information in memory, mediated by the VLPFC. In particular, the control processes that may identify, elaborate, filter or refine cues used to locate information in memory may be important for cognitive insight. Future works may include measures of cognitive flexibility and memory retrieval to test this hypothesis. Both measure of cognitive insight significantly associated with thickness in frontal regions outside of the VLPFC as well as in temporal and parietal cortices. In all cases, higher Self-Reflectiveness was correlated with greater cortical thickness, and higher Self-Certainty was associated with cortical thinning; thus the direction of both effects is consistent with previous cognitive insight-neuroimaging studies. Several of these regions may be of particular interest. For example, the precuneus has been previously associated with poor clinical insight in schizophrenia (Cooke et al., 2008), and is long known to be important for self-

processing operations (Cavanna and Trimble, 2006) including evaluating one's emotions (Ochsner et al., 2004) and one's psychological attributes (Kircher et al., 2002). The middle frontal gyrus has been linked to poorer clinical insight (Shad et al., 2004) and meta-cognitive insight (Spalletta et al., 2014) in schizophrenia, and the orbitofrontal cortex appears to be important for symptom attribution in people with psychosis (Buchy et al., 2012a; Shad et al., 2006). The inferior temporal cortex has also been linked to insight impairments in psychosis (Buchy et al., 2011; Cooke et al., 2008; Ha et al., 2004). The present findings extend previous research by suggesting that the neural underpinnings of cognitive insight also involve widespread frontal, temporal and parietal cortical regions. No significant correlations were seen between either Self-Certainty or Self-Reflectiveness and either total hippocampal volumes or subfield volumes. Only one other study has evaluated cognitive insight– hippocampal associations, and it is difficult to rule out effects of differences in sampling, such as the length of first-episode psychosis or the clinical profile of participants (e.g., positive or negative symptom severity), or imaging methodologies (manual tracing vs. automated extraction with FreeSurfer) that may have contributed to variance across

Please cite this article as: Buchy, L., et al., Cognitive insight is associated with cortical thickness in first-episode psychosis, Schizophr. Res. (2016), http://dx.doi.org/10.1016/j.schres.2016.02.026

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Table 3 Correlations between cognitive insight, hippocampal volumes and fornix fractional anisotropy. Structure

Hemisphere

Self-Reflectiveness

Self- Certainty

Total hippocampal volume Presubiculum CA1 CA2/3 Fimbria Subiculum CA4/dentate gyrus Hippocampal fissure Hippocampus Total hippocampal volume Presubiculum CA1 CA2/3 Fimbria Subiculum CA4/dentate gyrus Hippocampal fissure Hippocampus Fornix Fornix

Left Left Left Left Left Left Left Left Left Right Right Right Right Right Right Right Right Right Left Right

−0.04 (0.89) −0.11 (0.73) 0.03 (0.93) −0.01 (0.97) 0.40 (0.22) −0.37 (0.22) −0.09 (0.77) 0.25 (0.41) 0.54 (0.06) 0.18 (0.55) −0.04 (0.91) 0.44 (0.13) 0.11 (0.72) 0.42 (0.27) 0.22 (0.47) 0.17 (0.59) 0.38 (0.23) 0.19 (0.54) 0.47 (0.12) 0.36 (0.26)

0.59 (0.04) −0.31 (0.33) −0.18 (0.58) −0.03 (0.94) −0.33 (0.35) 0.46 (0.13) 0.09 (0.78) 0.20 (0.51) −0.26 (0.41) 0.18 (0.57) 0.05 (0.87) −0.06 (0.86) −0.10 (0.75) −0.41 (0.28) 0.08 (0.81) 0.01 (0.99) 0.39 (0.24) −0.20 (0.54) −0.35 (0.69) 0.18 (0.59)

Note. Results expressed as partial correlations with corresponding p-values in brackets.

studies. Further, no significant effects appeared between fornix fractional anisotropy and Self-Certainty in the current work. The only other study to evaluate associations between cognitive insight and fornix fractional anisotropy reported a positive relationship between fornix fractional anisotropy and Self-Certainty in a FEP sample (Buchy et al., 2012b). The scarce literature on this topic makes interpretations about the null result difficult. One study found no significant correlations between cognitive insight and either white matter macrostructure, as evaluated with voxel-based morphometry, or white matter microstructure, using DTI fractional anisotropy and mean diffusivity maps, in a sample of people with schizophrenia (Orfei et al., 2013). Perhaps a whole-brain approach using track based spatial statistics analysis could better reveal how properties of white matter microstructure align with individuals' level of cognitive insight. Our whole-brain cortical thickness analysis showed that higher Self-Certainty was associated with cortical thinness in widespread frontal, temporal and parietal regions; thus a broader approach may provide information about white matter anatomical connectivity between these regions. Several limitations should be noted. Results should be interpreted with caution given the small sample size. Despite the small sample size, cortical thickness results survived rigorous correction for multiple comparisons, and analyses were driven by a priori hypotheses. Lack of neurocognitive data precludes ability to examine relations between cognitive insight and verbal memory and executive functions as has been reported previously (Riggs et al., 2010), or evaluate their contribution to neuroanatomical effects seen here. Additionally, there is a growing body of literature on cognitive insight in non-clinical samples, and we are unable to evaluate group differences between people with a FEP and controls. Moreover, the same is relatively heterogeneous in terms of diagnoses and is comprised mainly of males, and these aspects may increase instability in observed results. Despite these limitations, results extend knowledge of the neural substrates of cognitive insight in a small FEP sample, by showing that Self-Certainty and Self-Reflectiveness are significantly associated with cortical thickness in fronto-temporo-parietal regions. Longitudinal studies will help to gain knowledge of how changes in SelfReflectiveness and Self-Certainty covary with neural structure over time. This represents an important step, as research has shown that other forms of insight can change over the first few years of a FEP, such that some people show persistently good or poor insight, while others lose or gain insight (Buchy et al., 2010a; Fennig et al., 1996; Saeedi et al., 2007). There is also research showing progressive brain

changes soon after the onset of a FEP (Fusar-Poli et al., 2012). Thus, longitudinal analyses may reveal variable courses of cognitive insight, and have the potential to reveal progressive neuroanatomical changes covarying with changes in cognitive insight in people with psychosis. Role of funding source The Mathison Centre had no further role in study design; in the collection, analysis and interpretation of data; in the writing of the report; and in the decision to submit the paper for publication. Contributors The first author performed behavioral and imaging analysis and wrote the first version of the manuscript. The second and sixth authors assisted in data collection and organization. The third and fourth authors assisted in conceptualizing the study. The fifth author assisted with imaging analyses. The seventh author oversaw the project from conception to completion and was responsible for all clinical components. All authors have contributed to the writing of the manuscript and approved the final version. Conflict of interest All authors declare no conflict of interest. Acknowledgements This study was supported by a Mathison Centre Pilot Research Fund Program awarded to Jean Addington, Signe Bray and Frank McMaster. Lisa Buchy is supported by a CIHR fellowship and Mariapaola Barbato is supported by a Mathison Centre postdoctoral fellowship. The authors thank staff at Seaman's Family MR Research Centre for assistance with data collection. We are thankful for all the people who participated in the study.

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Please cite this article as: Buchy, L., et al., Cognitive insight is associated with cortical thickness in first-episode psychosis, Schizophr. Res. (2016), http://dx.doi.org/10.1016/j.schres.2016.02.026

Cognitive insight is associated with cortical thickness in first-episode psychosis.

Compared to non-clinical subjects, people with psychosis show poor cognitive insight as reflected in low Self-Reflectiveness and high Self-Certainty. ...
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